F4S: Hi Jan Erik. Please, give us a brief introduction about yourself.
I did my PhD in applied mathematics at the Mathematical Imaging Group, Lund University, focusing on computer vision problems. After that I had a computer vision startup and worked as associate professor. Now I do computer vision at Apple in California.
F4S: Tell us the story behind your book “Programming Computer Vision with Python“.
I wanted to write a book with a low entry level that teaches enough computer vision to solve real world problems and build applications using open source and free software. I was inspired by books like Programming Collective Intelligence by Toby Segaran and thought that something like this should be written for computer vision.
Initially it started from a series of blog posts at janeriksolem.net that grew into a half-finished book. I then posted updates online for about six months, collecting feedback and comments before finalizing the book with O’Reilly.
F4S: Who will benefit from reading it?
The book is really meant as an entry point to hands-on computer vision for students, researchers and enthusiasts. Anyone curious about getting started with computer vision or learn how to use Python for their favorite computer vision problem will benefit from this book.
F4S: How will you describe your experience writing the book?
It was a lot of fun. I wanted the book to be self-contained and have complete working code for all examples so I had to implement everything I wanted to write about. In the process I learned some new things myself.
Writing the book also took longer time than I had hoped. I wrote during evenings and weekends when I could find time since I worked full-time during the whole book project.
F4S: Have you published other FLOSS related books?
No. There is something coming though…
F4S: Do you have plans for other books?
I’m co-authoring a book on scientific computing with Python. No release date set yet.
F4S: Why is free/libre open source scientific software important for your field?
From a scientific point of view it is important as part of being able to reproduce results and claims. Building your research on top of an open source stack removes barriers for others who want to reproduce and build on your results.
From a developer’s and researcher’s point of view, having open source building blocks in place helps focus resources on the important parts, the actual research, and less on underlying “plumbing”. A vibrant community behind the software you use is also a great help sometimes.
F4S: Which projects, books, blogs or sites related to open source software for science can you recommend?
For computer vision specifically, OpenCV (http://opencv.org/) is a fantastic project with a great community and user base. The scikit-learn project (http://scikit-learn.org/) is great if you are into machine learning.
F4S: Where people can contact you?
F4S: Thank you Jan Erik for allowing us to share your work with our readers.
- A Primer on Scientific Programming with Python, an interview with author Hans Petter Langtangen
- Open Computer Vision Library 2.4.0 for Android released
- Open Computer Vision Library 2.4.0 for Linux and Windows released
- Open Computer Vision Library 2.4 beta and new developer site
- Python(x, y) 220.127.116.11 released